Suman Vadlamani
Biographic Data
| ID | 7508723 |
|---|---|
| NAME | Suman Vadlamani |
| GIVEN NAMES | Suman |
| FAMILY NAME | Vadlamani |
| SIGNATURE | VADLAMANI S |
| AFFILIATIONS | University of Texas Health Science Center at Houston, Houston, TX, United States of America |
| VERIFIED | No |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2024 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
AI’s ongoing impact
Objective. To assess the effects of the current use of artificial intelligence (AI) in women’s health on health equity, specifically in primary and secondary prevention efforts among women. Methods. Two databases, Scopus and PubMed, were used to conduct this narrative review. The keywords included “artificial intelligence,” “machine learning,” “women’s health,” “screen,” “risk factor,” and “prevent,” and papers were filtered only to include those…
Intersecting social determinants of health among patients with childcare needs
This analysis of SDOH approximated by SVI showed actionable differences, potentially transportation barriers, among patients with childcare needs who utilized a health system-integrated childcare facility and patients who did not utilize services. Furthermore, residual unmet social needs among patients who utilized the facility demonstrate the multifactorial nature of social risk factors experienced by patients with childcare needs and opportunit…
No prominent works on this page.
Intersecting social determinants of health among patients with childcare needs
This analysis of SDOH approximated by SVI showed actionable differences, potentially transportation barriers, among patients with childcare needs who utilized a health system-integrated childcare facility and patients who did not utilize services. Furthermore, residual unmet social needs among patients who utilized the facility demonstrate the multifactorial nature of social risk factors experienced by patients with childcare needs and opportunit…
AI’s ongoing impact
Objective. To assess the effects of the current use of artificial intelligence (AI) in women’s health on health equity, specifically in primary and secondary prevention efforts among women. Methods. Two databases, Scopus and PubMed, were used to conduct this narrative review. The keywords included “artificial intelligence,” “machine learning,” “women’s health,” “screen,” “risk factor,” and “prevent,” and papers were filtered only to include those…
Environmental health (2 works) · Gerontology (2 works) · Health care (2 works) · Medicine (2 works) · Nursing (2 works) · Population (2 works) · Psychology (2 works) · Public health (2 works) · Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare and Education (1 work)